The JPL EDRN Informatics Center develops data-intensive informatics solutions to support the Early Detection Research Network in capturing, processing, managing, distributing and analyzing data from cancer biomarker research. The earlier cancer is detected, the more effective the treatment. That's why it's the mission of the Early Detection Research Network to research biomarkers. Biomarkers are indicators of disease or the potential for disease. Managing the enormous amount of knowledge, information, and data that goes into biomarker research requires a herculean effort. That's why EDRN turned to Jet Propulsion Laboratory to become EDRN's Informatics Center. JPL and NCI have worked together to build a leading edge, national, bioinformatics network for the capture, management, distribution and analysis of cancer research data. This network is based on leveraging the technologies, capabilities, and expertise of JPL in building scientific data-intensive systems across multiple disciplines. This includes the use of Apache OODT, originally developed by JPL, and now part of the Apache Software Foundation. OODT provides an open source, data management framework for building the EDRN Knowledge System or EKE. EKE is a virtual knowledge-base of biomarkers, studies, publications, and resulting science data from EDRN research that is integrated and powered by a semantic-based search. While the system appears fully integrated, it is really a virtual data system with data distributed at a national level. The infrastructure developed by the EDRN Informatics Center (IC) will not only support EDRN over the next five years but is well positioned to support other programs currently being developed under the leadership of the Cancer Biomarkers Research Group (CBRG). One such program is the Molecular and Cellular Characterization of Screen-Detected Lesions (MCL) consortium. The MCL is a Consortium that consists of independent, multi-disciplinary teams to conduct comprehensive molecular and cellular characterization of tumor tissue, cell, and microenvironment components to distinguish indolent from aggressive cancer among screen-detected early lesions, as well as between screen-detected from interval and symptom-detected cancers.